Automated image processing to quantify neurite growth in Luhmes human neuronal precursor cells

Abstract

Chemicals that specifically inhibit human neurite outgrowth pose a hazard to the developing nervous system. Identifying such chemicals remains a major challenge in biological research. In response to the need for more efficient methods to identify potential developmental neurotoxicants, an image processing framework is presented that allows to automatically quantify neurite growth in LUHMES human neuronal precursor cells. For this purpose, a H-33342 staining is used in order to identify the outline of the nucleus of each neuronal cell. Based on this outline, a region growing approach is performed that expands the soma until an intensity threshold is reached, which allows to quantify the number of cells with neurites. The results demonstrate that our image processing framework can rapidly quantify chemical effects on neurite outgrowth. Concentration-response data for neurite outgrowth allows for the determination of the specificity of chemical effects on developing neuronal cells. Further studies will examine the utility of the approach for other cell-based assays of neurite outgrowth.